strategic rewards systems: a contingency model of...

STRATEGIC REWARDS SYSTEMS: A CONTINGENCY MODEL OF PAY SYSTEM DESIGN

BRIAN K. BOYD

Department of Management

College of Business Arizona State University Tempe, AZ 85287-4006

+01 602 965 4781 [email protected]

ALAIN SALAMIN

Department of Management Ecole des HEC

University of Lausanne 1015 LAUSANNE-DORIGNY

Switzerland

and

Compensation Development FIRMENICH SA Rue de la Bergère 1218 MEYRIN 2

Switzerland [email protected]

Keywords: Compensation, contingency theory, managerial discretion, international

Strategic Management Journal, forthcoming

© JOHN WILEY & SONS

Strategic Reward Systems / 2

STRATEGIC REWARDS SYSTEMS: A CONTINGENCY MODEL OF PAY SYSTEM DESIGN

ABSTRACT

A limited number of studies have addressed the idea of “strategic” reward systems – the

matching of compensation systems to a firm’s strategy. Prior research on this topic has been

confined to US firms, however, and a number of key questions remain unanswered. Using a

sample of 917 employees from two large Swiss financial institutions, we found that pay systems

are linked with divisional strategic orientation, but in a different form than prior studies.

Additionally, we identify hierarchical position as an important variable in the tailoring of reward

systems. Hierarchy has a significant main effect on pay plan design, and an interactive effect

with strategic orientation.

We would like to thank Sydney Finkelstein and Luis Gomez-Mejia for helpful comments on an

earlier draft of this paper.


An organization’s employees provide an important basis for a sustainable competitive

advantage: Socially complex – i.e., people based – resources are considered more durable and

less susceptible to imitation than other types of assets (Barney, 1991). As such, the strategic

management of human resources can play a key role in an organization’s survival. A firm’s

compensation plan plays a prominent role in recruiting, motivating, and retaining employees, and

thus is central to building a durable advantage.

Consistent with this perspective, early compensation theorists (e.g. Salter, 1973)

proposed that firms should match their compensation systems to their strategies. The matching

hypothesis has been generally supported, with empirical studies of diversification (e.g. Kerr,

1985), type of product market strategy (e.g. Gupta & Govindarajan, 1984), and type of industry

(Galbraith & Merrill, 1991). However, many of these early studies emphasize beneficial

strategy-compensation combinations versus an explicit focus on fit between strategy and

compensation (Rajagopalan, 1997). Additionally, there have been mixed results across studies

(Balkin & Gomez-Mejia, 1990; Rajagopalan & Finkelstein, 1992), and questions regarding the

generalizability of findings to date.

We make multiple contributions to existing research on strategic rewards. First, we

provide a better understanding of the role that managerial discretion plays in the design of

reward systems. Two studies have argued that managerial discretion is a key factor in the

matching of pay practices to strategy (Rajagopalan & Finkelstein, 1992; Rajagopalan, 1997). In

these papers, a firm’s strategic orientation – measured via the Miles and Snow (1978) strategy

typology – is viewed as a proxy for discretion. We confirm those findings, and also suggest that

discretion varies substantially across levels of the managerial hierarchy. We also find that,


separate from their main effects, strategic orientation and hierarchy have a strong interactive

effect on multiple aspects of pay plan design.

By testing our hypotheses with 917 employees from two large, Swiss financial

institutions, we also provide an important test of the generalizability of prior findings to non-U.S.

firms. Such studies have been identified as a prominent omission of current research on human

resources: “Finally, the bias in compensation research toward American companies threatens the

generalizability of this research to global settings. Until comparative research is conducted, it

will be difficult to determine how this bias has influenced current theory and research. (Gomez-

Mejia & Wiseman, 1997: 364)”. Additionally, the results of prior international comparisons has

been mixed: For example, Pennings (1993) concluded that agency models of incentives were not

applicable to certain European contexts. In contrast, Roth & O’Donnell (1996) found support for

an agency model of incentives, but that the effect varied at different levels of the organizational

hierarchy.

LITERATURE REVIEW AND HYPOTHESES

Linking Pay and Strategy

As shown in Table 1, there are a number of empirical studies which have examined the

matching of pay plan design to strategy. The bulk of these studies have used diversification as

the measure of strategy. More recent studies, though, have examined the role of a firm’s

strategic orientation (Rajagopalan and Finkelstein, 1992; Rajagopalan, 1997). The level of

diversification is a firm-level variable, while strategic orientation can vary substantially across

divisions of a firm. As such, the latter variable has practical relevance to a wider range of human

resource managers – i.e., those at both corporate and division levels. Additionally, strategic


orientation has seen comparatively less attention than diversification in prior compensation

studies. Therefore, our focus is on the matching of pay plan design to strategic orientation.

An important contribution to clarifying the fit between compensation and firm strategy

originated in the work of Balkin and Gomez-Mejia (1987), who found that the effectiveness of

pay systems was contingent upon firms’ strategic characteristics such as size, stage in the

product life cycle, and technology emphasis. In a subsequent study (Balkin & Gomez-Mejia,

1990), the authors explored the implications of corporate and SBU strategies for pay package

design. They classified firms by their degree of diversification, and the corresponding SBU by

their growth vs. maintenance orientation. The authors suggested that both corporate and SBU

strategies are significant predictors of the pay package design. Moreover, firms pursuing growth

strategy placed more emphasis on incentive pay. However, several questions remain

unanswered: is the degree of leverage (ratio of incentive to base pay) also related to firm and

SBU strategies? Do these findings hold if we use other taxonomies of strategic orientation? Does

organizational strategy affect the pay of all job clusters equally?

These questions are partially addressed in a study by Rajagopalan and Finkelstein (1992),

who reported that strategic orientation has significant effects on compensation practices. Firms

with discretionary strategic orientations made greater use of outcome-based rewards mechanisms

(incentive and options plans), tied greater proportions of pay to performance, and offered higher

overall compensation levels than did firms with more conservative strategic orientations.

However, several questions were raised by their findings: their results for base pay were counter

to those of Balkin and Gomez-Mejia (1990), and results on long-term incentives plans were


contrary to expectations. Finally, given the highly regulated nature of their sample – electrical

utilities – it is unclear how well their sample mirrors that of other populations.1

More recent studies have yet to provide definitive conclusions on the subject. Wright,

Smart and McMahan (1995) offer empirical support for links between strategies and human

resources characteristics, but the study has limited relevance for most organizations, since the

sample was made of basketball teams. Barkema (1996) concluded that top manager inclination to

change the current strategy in the direction of more growth is curbed by their share holdings, but

not by their bonuses. These results suggest that growing SBUs do not link bonus to strategy;

which is contrary to other studies on this topic. Finally Rajagopalan (1997), in a subsequent

study, found global support for the fit between compensation and firm strategy. These results

were also based on a sample of highly regulated utilities, so the question of generalizability

remains unanswered.

In summary, prior research has produced preliminary support for the notion that firms

match their pay systems to their strategic orientation. Concurrently, other studies have found that

a firm’s strategic orientation can shape many aspects of internal structure and processes. For

example, managerial philosophies (Zahra, 1987), planning systems (Boyd & Reuning-Elliott,

1998; Odom & Boxx, 1988; Shortell & Zajac, 1990) and human resources practices (Slocum et

al., 1985) have all been found to vary according to strategic orientation. Consequently, the

matching of pay and strategy has strong theoretical and empirical justifications.

1 A comparison of strategic orientation in their sample versus other studies reveals marked differences; presumably

due to the high levels of government regulation for electrical utilities. For example, no firms in their sample were Analyzers, while Analyzer is the most commonly reported strategy in several studies (e.g., Boyd & Reuning-Elliott, 1998; Balkin & Gomez-Mejia, 1990; James & Hatten, 1995; Shortell & Zajac, 1990). Similarly, none of these studies reported having any Reactors; in comparison, 34% of firms in the Rajagopalan and Finkelstein sample were classified as Reactors. Recognizing this limitation, the authors concluded there was a need for replication using samples with more balanced strategy categories (Rajagopalan & Finkelstein, 1992: 139), as well as in more competitive markets (Rajagopalan, 1997: 782).


Strategic orientation

To categorize business-level strategies, we will adopt the Miles and Snow framework

(1978), as it is one of the most commonly studied typologies (Zahra & Pearce, 1990). Their

framework is predicated on three underlying domains: entrepreneurial, administrative, and

technical. The entrepreneurial domain concerns the firm’s markets, the administrative domain

focuses on strategy execution, and the technical domain relates to underlying product and

process technologies. Miles and Snow then distilled three primary approaches for addressing

these domains: Prospectors have a strong market orientation, and emphasize new product

development and early entry. Defenders, in contrast, have a strong internal orientation, and

emphasize cost efficiency and a stable set of products. Analyzers follow a hybrid strategy,

combining elements of both Prospectors and Defenders.

Rather than treat the Miles and Snow strategies as discrete categories, we follow the

convention of recent research (Shortell & Zajac, 1990; Boyd & Reuning-Elliot, 1998), who

subsumed them within a continuum of ‘orientation towards change’. On this continuum,

Prospectors represent a strong orientation towards change, and Defenders a weak orientation. A

continuous measure offers a richer form of data than categorical measures; hence we use the

‘strategic orientation’ label in both our hypotheses and measurement. However, we will use the

Prospector and Defender categories as a shorthand when developing our rationale, as they are

widely understood, and serve as anchor points of the measure. Strategic orientation will be

analyzed relative to key dimensions of the compensation package: compensation level (base

salary), incentives (bonus), and risk exposure (pay mix) (Gomez-Mejia, 1994).

The Prospector type is characterized by uncertainty, growth perspectives, risks,

innovation, and considerable managerial discretion (Miles & Snow, 1978; Hambrick & Snow,


1989; Snow & Hrebiniak, 1980). On the other hand, Defenders are defined by more stable

demand, pressure for lower costs and prices, reliable quality, and less managerial discretion

(Miles & Snow, 1978; Hambrick & Snow, 1989; Snow & Hrebiniak, 1980; Rajagopalan &

Finkelstein, 1992).

Strategic orientation and discretion

Rajagopalan (1997: 764) has proposed that the firm’s strategic orientation – and, by

extension, the Miles and Snow strategy categories – are proxies for managerial discretion: “A

firm’s strategic orientation has direct implications for the type and extent of managerial

discretion available to key executives within the firm.”

Managerial discretion refers to the latitude of options top managers have in making

strategic choices. Discretion has been applied empirically in a broad range of settings and

operationalizations. For instance, discretion has been measured at the industry (Finkelstein &

Hambrick, 1990), firm (Finkelstein & Boyd, 1998), and individual (Carpenter & Golden, 1997)

levels. Similarly, discretion has been measured as categories (Finkelstein & Hambrick, 1990),

multiple indicators (Finkelstein & Boyd, 1998), survey measures (Carpenter & Golden, 1997),

and expert assessment (Hambrick & Abrahamson, 1995). It has been studied directly, and

inferred indirectly (e.g., Rajagopalan & Finkelsteiin, 1992; Roth & O’Donnell, 1996). This

broad range of prior use would suggest that discretion is fairly robust – i.e., applicable to a

variety of contexts and measurement schemes.

Compensation plans that reward risk-seeking and long-term decision horizons seem

appropriate for Prospectors because their strong incentive components reduce risk-aversion by

managers (Holmstrom, 1979; Larcker, 1983) and minimize monitoring costs (Walsh & Seward,

1990). Conversely, pay packages oriented toward rewarding efficiency, short-term objectives


and past performance (Galbraith & Merrill, 1991) appear more suited to Defenders since their

strong emphasis on base salary and benefits motivate less risky behaviors (Balkin & Gomez-

Mejia, 1990; Hambrick & Snow, 1989) and foster adherence to past norms (Rajagopalan, 1997).

As a result, firms in Prospector positions should use larger incentives than Defenders

companies, and their pay mix should reflect a higher leverage than Defenders ones. Additionally,

strategic orientation should affect base pay as well. Since Prospectors strategies increase

outcome uncertainty (Hambrick & Snow, 1989), higher base salaries are needed to offset this

risk and attract and retain managers (Rajagopalan & Finkelstein, 1992). Similarly, since most

Defenders compete on a basis of process efficiency and cost containment, there are typically less

financial resources available, leading to lower base salaries (Hambrick & Snow, 1989).

Consequently, our first hypotheses postulate a fit between compensation and strategic

orientation:

H1: Base salary will be positively related to strategic orientation.

H2: Bonus pay will be positively related to strategic orientation.

H3: Pay mix will be positively related to strategic orientation.

The Role of Organizational Hierarchy

The contribution of our first three hypotheses is to replicate prior research in a different

setting, and to address inconsistencies between prior findings. In this section, we extend on prior

research by introducing hierarchy as a new variable in the study of strategic rewards. As shown

in Table 1, the issue of organizational hierarchy has not been an explicit focus of prior studies,

except from a sampling perspective. Of the studies on strategic orientation, two have addressed

the top management team (Rajagopalan & Finkelstein, 1992; Rajagopalan, 1997), and one

addressed all employees (Balkin & Gomez-Mejia, 1990). In contrast, studies on diversification


have not addressed CEO and TMT pay; rather, these studies have sampled division-level

managers and those lower in the hierarchy.

There are discrepancies in the findings of prior studies, and hierarchy is a potential

omitted variable which may explain such differences. For example, the use of incentives among

firms pursuing growth-oriented strategies is very different for TMTs (Rajagopalan & Finkelstein,

1992) than for lower levels of the organization (Balkin & Gomez-Mejia, 1990). Similarly, in the

context of diversification, very different findings on pay practices have been reported for

corporate-level (Napier & Smith, 1987) versus lower-level managers (Berg, 1973; Pitts, 1976).

Additionally, within the narrower context of TMTs, some studies have found systematic

differences in pay packages for CEOs versus other top managers (Murphy, 1985; Rajagopalan &

Prescott, 1990). Thus, there is an empirical basis to infer that hierarchy may be an important

moderator in the design of pay systems.

Hambrick and Snow (1989) argued that a strategic compensation system should not treat

general managers as a homogeneous lot, given the overall number and diversity of general

management positions. Additionally, Milkovich (1988) noted that, since a broad range of

employees are responsible for executing strategies, reward systems for these staff are of strategic

importance. However, short of anecdotal data, no study has addressed this statement to date. As a

result, a question raised by Balkin and Gomez-Mejia (1990: 164) still remains unanswered: “do

strategic factors explain the pay policies of executives and sales representatives, and non

strategic factors explain the pay policies that affect pay for production workers and clericals?” In

other words, does the firm’s strategy play a differing role in setting compensation as we move

throughout the hierarchy?


Previously, Rajagopalan argued that strategic orientation is a proxy for discretion. Here,

we suggest that hierarchical position may also be an indicator of discretion. Hambrick and

Finkelstein (1987) focused their discussion exclusively on top managers. Yet, the roots of

discretion – including determinism, managerial constraints, and superior-subordinate relations2 –

clearly apply to employees beyond top managers. If discretion is loosely defined as ‘latitude of

action’, do higher level managers have greater latitude than those below? If so, what then are the

implications for pay plan design?

Sitting at the ‘strategic apex’ of the firm, the chief executive clearly has the greatest

opportunity to take action. By virtue of hierarchical position, the top executive has the strongest

levels of reward, coercive, and legitimate power (Mintzberg, 1983). As a result, the top

executive has broad latitude for action, being subordinate only to external powers such as the

board and financial markets. Similarly, members of the top management team have considerable

latitude, lessened only by their subordinance to the CEO. It is not surprising, then, that most

discussions of managerial discretion are confined to senior staff.

Mintzberg (1983: 126), however, argues that even the lowest manager has some

discretion: “We see shades of all of the same bases of power in the middle line. Each manager

is, by definition, in charge of an organizational unit – a division, department, factory, shop, or

whatever. And within that unit he is like a mini-CEO, with many of the same types of power

over it that the CEO has over the whole organization.” Concurrently, though, these managers

will experience less latitude as they are increasingly subject to bureaucratic controls. Thus, rather

than discretion ‘ending’ at the upper echelon, it is likely rather to flow down the hierarchy, albeit

with greater and greater restriction.

2 For a brief review, see Pfeffer and Salancik’s (1978: 244-47) discussion of discretion and organizational decision-


That said, can we extend discretion further down the hierarchy to non-managerial staff?

Pfeffer and Salancik (1978) cautioned against the notion of powerless subordinates, noting that

these staff “frequently controls resources or performance critical to the activities of the manager

(1978: 246).” Additionally, professional staff typically possess specialized skills and knowledge,

which limits the administrative controls that can be placed on them. Consequently, Mintzberg

noted that professional staff “must be given considerable discretion in their work, and so come to

amass a great deal of power (1983: 132).” Similarly, Finkelstein and Hambrick (1990) applied

discretion to a study of strategic decision-making. While they found strong support for their

hypotheses, they also noted that future research should address a broader spectrum of the

hierarchy, as “lower level employees may be influential in professional firms or in those with

emergent strategies (1990: 500).” Echoing our rationale, Carpenter and Golden (1997) reported

that hierarchical position was the strongest covariate of an employee’s perception of their own

discretion.

Our first three hypotheses proposed that levels of all three pay components would be

higher in more discretionary contexts, i.e., in divisions with a strong orientation toward change.

If hierarchy is indeed a proxy for discretion, then we would expect this variable to have a similar

effect on pay plan design. Therefore, we propose:

H4: Base salary will be positively related to hierarchical position.

H5: Bonus pay will be positively related to hierarchical position.

H6: Pay mix will be positively related to hierarchical position

Thus far, we have argued that both strategic orientation and hierarchical position are

proxies for discretion. And, consistent with prior research (Rajagopalan & Finkelstein, 1992;

Finkelstein & Boyd, 1998), we expect more emphasis on both base and incentive pay at higher

making.


levels of discretion. In our final hypotheses, we suggest that there will be a synergisitic effect as

well – i.e., that strategic orientation and hierarchy will have both main and interactive effects.

Therefore:

H7: Strategic orientation and hierarchy will have an interactive effect on base salary.

H8: Strategic orientation and hierarchy will have an interactive effect on bonus pay.

H9: Strategic orientation and hierarchy will have an interactive effect on pay mix

METHOD

Sample

To enhance the generalizability of our findings, we collected data from two independent

Swiss financial institutions. Using company records, we obtained data on compensation and

demographic variables, for a total of 917 employees across the two firms. To ensure a representative

group of employees, we used a random sample, stratified by each strategic business unit and

hierarchical position. Within each SBU and hierarchical level, we sampled a proportional number

of subjects, based on the size of that pool. A review of both firms indicate that divisions operate

autonomously (Roth & O’Donnell, 1996): SBUs have control over production activity and

innovation, marketing, and strategy. Additionally, profit and loss is calculated at the division level .

Sample 1. The firm was divided into five Strategic Business Unit: Private Banking (PB),

Investment Banking (IB), Institutional Asset Management (IAM), Retail Banking (RB) and

Logistic (LOG). In 1996, the bank employed a total of nearly 30,000 employees. In our sample,

approximately two-thirds of the employees were male. The average age was 38 years, and mean

tenure was 13 years. We sampled 401 employees from this firm.

Sample 2. The second firm was divided into five slightly different strategic divisions: Private

Banking (PB), Investment Banking (IB); Institutional Banking (IAM), Retail Banking (RB) and


Corporate Clients (CC). In 1996, the bank employed nearly 40,000 employees worldwide. The

male/female ratio of our sample was .69/.31, the average age was 39 years, and mean tenure was 12

years. We sampled 516 employees from this firm.

Measurement

Compensation. Data were collected from personnel records for two compensation variables:

total base salary (using a log transform to normalize the distribution), and total bonus pay. From

these, we computed the degree of leverage, defined as the ratio of bonus to base pay. By using

archival measures of pay, we are free from problems of nonrespondent or common method bias. A

comparison of means for these variables determined that neither base salary (t=1.28, p=.20) nor

bonus pay (t=0.5, p=.0.62) differed significantly across samples

Strategy. Next, we coded a measure of strategic orientation for each business units. This

measure subsumes the Miles and Snow strategic types under a continuum of ‘orientation towards

change’. On this scale, Defenders (coded ‘1’) represent the low orientation towards change,

Prospectors (coded ‘3’) the high orientation towards change, and Analyzers (coded ‘2’) the

midpoint. Previously published analyses have demonstrated the reliability and validity of this

continuum measure, including its correspondence with a number of archival indicators (Boyd &

Reuning-Elliott, 1998; Shortell & Zajac, 1990).

Many studies have used either investigator or other expert opinion to assess a firm’s

strategic orientation (e.g., Meyer, 1982; Hambrick, 1983; Slocum, et al., 1985; Chaganti &

Sambharya, 1987). As part of a broader project, one of the authors has been hired in the Human

Resources Department of the Sample 1 bank for about 18 months, working across all five SBUs,

including interviews with all of the subjects mentioned above, as well as with other executives and

directors. Based on a combination of expert interviews and archival sources, and prior to this


research, the author evaluated each of the SBUs on multiple criteria, such as orientation towards

new products and innovation, stage in the life cycle, market context, investment allocations,

orientation toward costs, and strategic objectives3.

Based on this information, each SBU was rated on the Shortell and Zajac orientation toward

change scale. Next, this paper’s co-author also classified the divisions, using descriptions of each

area. Finally, the strategic orientation scores for each division were reviewed and vetted by key

decision-makers within the firm. A similar process was used to evaluate the divisions of the second

sample.

Hierarchy. Both companies used the same hierarchical structure with identical levels and

designations. Position in the hierarchy was coded as a continuous variable, ranging from 0

(Employees) to 7 (Managing Director). We chose to measure hierarchy as a continuous variable

versus a set of dummy indicators since the latter are less parsimonious, less powerful, and more

problematic in the study of interaction effects (Cohen & Cohen, 1975).

Control variables. We included five control variables to provide a meaningful test of

hypotheses, and to avoid omitted variable problems (Barkema, 1996). Our controls included both

individual and division level factors. At the individual level, we controlled for age, gender (0/1

dummy variable, with ‘0’ for male), and tenure. At the division level, we controlled for division

size (number of employees) and financial performance (measured as EBIT).4 A comparison of

means indicated no significant differences between the two samples for any of our control variables,

3 We did not attempt to weigh these factors into any sort of cumulative or index score, as there was no empirical

basis for doing so. Rather, we collected this information solely to provide a more detailed context for assigning business units to levels of the strategic orientation continuum.

4 We did not include controls for education, due to differences in the Swiss educational system as compared to the United States. All employees sampled in the study were considered to be professional or white-collar employees; none of our subjects were clerical or secretarial staff. Additionally, each of our subjects had completed, at the very least, an apprenticeship program in the banking profession lasting four years; a rough analogue for collegiate education in the States.


with the exception of prior performance (t=6.96, p=.001). Data for the hierarchy measure and all

control variables were obtained from company records.

Analysis

As with similar studies, there is the potential for colinearity between hypothesized predictors

and control variables. To control for this potential, we follow the lead of other studies (e.g., Gomez-

Mejia, 1992; Roth & O’Donnell, 1996) and used a hierarchical regression to test hypotheses. By

comparing nested models, and entering predictor terms after all controls were introduced, we offer a

conservative test of the unique variance explained by our hypotheses.

Table 4 reports three stages of models: First, we enter all control variables. Second, we

introduce the main effects for strategic orientation and hierarchy concurrently. Finally, we

introduce the interaction term between strategic orientation and hierarchy. Incremental F-statistics

were used to formally assess the improvement in explained variance at each step.

RESULTS

Descriptive information

Table 2 provides descriptive statistics for our variables. For comparison purposes, we

have included summary statistics for each of the two subsamples. To illustrate the potential

interaction between strategic orientation and hierarchy, we report more detailed statistics in

Table 3. This Table compares average levels of base salary, bonus, and leverage, for each

combination of strategic orientation and hierarchical level. For parsimony, we report this

information for subsample 1 only. As shown in the Table, levels of base salary do not vary

systematically by strategic orientation, except at higher hierarchical levels. In contrast,

Prospectors have the highest levels of bonus pay and leverage, regardless of hierarchical


position. Additionally, the differences between Defenders and Analyzers are minor, except for

upper levels. Interestingly enough, the discrepancy between the highest and lowest overall wage

in our sample represents a 13.5 coefficient (FTE converted base salary). For the highest and

lowest paid bonus, this coefficient raises to 1428.6.

Results of hypothesis tests

The regression models in Table 4 explain a substantial amount of variance in our

dependent variables: Adjusted R2 was 0.89 for base salary, 0.48 for bonus, and 0.53 for leverage.

Incremental F-tests reported that both main effect and interaction models were a statistically

significant improvement. The Sample variable was significant for both bonus and leverage

models. Therefore, while levels of base pay are comparable across the two firms, our second

sample firm offered significantly lower (p=.001, both models) levels of bonus pay and leverage.

Base salary. Strategic orientation, hierarchy, and the interaction term were all significant

(p=.01 or greater), and in the expected direction. Thus, hypotheses for base salary were fully

supported. A graphic representation of the interaction in shown in Figure 1.

Bonus pay. All three independent variables were significant at the p=.001 level. The

relationship was more complex than for base salary, however. In the main effect model, the

coefficient for strategic orientation was nonsignificant, while hierarchy had a coefficient of 0.70

(p=.001). When adding the interaction term, the coefficient for hierarchy drops to 0.23 (p=.001),

and strategic orientation has a negative coefficient of -.22 (p=.001).

Initially, it would appear that the effect for strategic orientation is counter to expectations.

However, a surface map, shown in Figure 2, helps to clarify the relationship. The graph shows

that the highest bonus levels are at the top of the hierarchy, and in divisions with a strong change

orientation. At low levels, though, strategic orientation has a minimal effect on bonus pay. In


other words, sample firms offer more bonus pay in change oriented divisions; however, this

matching is quite weak at lower levels, and quite strong at upper levels.

Leverage. The findings for this variable closely resemble those of bonus pay, including

the same crossed interaction term. The surface map of the contingency relationship is shown in

Figure 2, and differs only slightly in form from that of bonus pay. On average, leverage is higher

in change oriented divisions, and at upper levels of the hierarchy. Again, tailoring is quite

strong for upper levels, and fairly minimal at lower levels.

DISCUSSION Research Findings

Our study offers some valuable insights into the design of strategic reward systems. Prior

work has found that firms to tend to align their pay systems to their strategy, yet only a few

studies (e.g., Rajagopalan & Finkelstein, 1992; Rajagopalan, 1997) have explicitly explored the

link between strategic orientation and compensation plan design. A comparison of our results

with prior studies is shown in Table 5. Our findings provide a useful confirmation and extension

of this nascent line of inquiry. Specifically, we found that strategic orientation affects the pay of

all employees, not just top managers. Additionally, orientation affects multiple aspects of the

compensation plan, and this link holds – at least for our two sample firms – outside the US.

A second major contribution to theory is the role of hierarchy. Our findings indicate that

the hierarchy component is an important element of the way firms design reward systems. Prior

research (Balkin & Gomez-Mejia, 1990; Rajagopalan & Finkelstein, 1992) concluded that firms

match their pay plans to strategic orientations. While our results echo the overall conclusion of

these studies, there are also some important differences. First, the magnitude of the strategic

orientation main effect varies with and without including the interaction term. Consequently,

interpretation of the main effect, by itself, is inherently misleading. Second, the strong


significance of the hierarchy variable – both main and interaction effects – indicates that this

relatively ignored variable warrants further attention.

While levels of managerial discretion are likely to increase substantially as one ascends

the corporate hierarchy, very little work has addressed the intersection between hierarchy and

discretion. Three key points emerge from our analysis: First, our study extends other work

(Finkelstein & Boyd, 1998; Hambrick & Snow, 1989) which has suggested that managerial

discretion is a major driver of pay systems. Specifically, our findings demonstrate that discretion

is applicable to a broader range of employees than previously studied. More importantly, the

interaction term demonstrates that firms weigh discretion and strategic orientation jointly when

designing pay systems. Finally, our analysis also provides evidence that the discretion construct

is generalizable to non-US firms.

Implications and Future Research

Unlike Bonus and Leverage, the factors influencing Base Salary seem to be very well

delimited, since our control variables alone explain a substantial porportion of the variance.

Thus, Base Salary can be viewed as more determined by individual characteristics (gender, age,

hierarchical position) than by strategic orientation. However, the inclusion of hierarchy and its

interaction term double the levels of explained variance. Given this fact, Base Salary, even if still

strategic, tend to be is more static and more difficult to use as a strategic leverage.

In contrast, Bonus is largely explained by Strategic Orientation, Hierarchy and the

interaction, which are under the control of the top management. As individual factors have little

effect on the bonus, it is more flexible and easier to adapt to a strategic orientation.

Consequently, Bonus should be considered as the favorite strategic compensation weapon, and

since allying consistency and flexibility is one of the most challenging task in designing the pay


system, we would advocate to rely on Base Pay to preserve consistency, and on Bonus to foster

flexibility.

One limitation of this paper is that we offer only a descriptive test of theory – i.e., what

factors are found to explain the design of compensation plans. Equally interesting, and largely

untested, is a normative analysis – i.e., what the implications of this ‘matching’ between strategy

and pay systems for performance outcomes?

This question could be explored at multiple levels. For example, one study found that,

while discretion was linked to executive pay, this relationship was stronger among high

performers (Finkelstein & Boyd, 1998). Similarly, then, it would be useful to compare whether

high and low performing firms – or SBUs – place differing emphasis on strategic orientation or

discretion when designing pay systems. Do high performing Prospectors use equally large base

salary cushions as their less effective counterparts? And, do they concentrate their incentives as

heavily at the top end of the hierarchy? Exploring how the matching of pay and strategy today

affects tomorrow’s performance would provide valuable insights into the optimum design of

reward systems.

A second approach would be to study this topic at a more fine-grained level. Our

hypotheses assume that a specific pay system – i.e., the cushion of a large base salary, plus

generous incentives – will encourage a level of risk-taking appropriate for a Prospector.

However, given the nature of our data, we are unable to observe either attitudinal or behavioral

correlates of these pay practices. It would be fruitful, then, to examine how such rewards affect

individual attitudes towards risk, and actual risk-taking behaviors. Additionally, a panel design

would help explore this issue more fully; for instance, how dynamic are the relationships

between these variables?


Finally, the significance of the hierarchy effect – both main and interaction –

demonstrates that we would have a substantial omitted variable problem had it not been included

in our analysis. As we noted earlier, there are a number of strategic pay topics which have

reported conflicting results when hypotheses have been tested at different hierarchical levels

(e.g., Rajagopalan & Finkelstein, 1992 versus Balkin & Gomez-Mejia, 1990; or Napier & Smith,

1987, versus Pitts, 1976). So, it would be worthwhile to revisit these analyses, and determine

whether hierarchy helps to resolve these inconsistencies.

CONCLUSION

The notion that firms match pay systems to corporate strategies has been widely held, but

only rarely tested. Our study provides a useful confirmation and extension of prior studies.

Based on our sample of two Swiss institutions, we conclude the following: (1) The role of

strategic orientation in allocating pay is more complex than previously believed; (2)

Organizational hierarchy plans an important role in this process; both independently, and in

conjunction with strategic orientation; (3) The stability of our findings across firms, and the

similarities to studies of US firms, suggest that US-based models of compensation may be more

generalizable than previously thought.


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TABLE 1

SUMMARY OF RELEVANT RESEARCH

Study Sample Level Pay Data Time Strategy Categories

Findings

(a) Studies of strategic orientation

Balkin & Gomez-Mejia (1990)

192 HR managers, cross-industry

All employees

Survey Cross-section

Dynamic growth (35%) Maintenance (65%)

Growth emphasize incentive pay, Maintenance emphasize cash

Rajagopalan & Finkelstein (1992)

50 electrical utilities

5 top paid executives

Archival Pooled cross-section

Prospectors (28%) Defenders (38%) Reactors (34%)

Strategic orientation associated with higher cash and bonus pay, greater use of incentives.

Same findings for CEO and TMT members.

Rajagopalan (1997)

50 electrical utilities

5 top paid executives

Archival Pooled cross-section

Prospectors (28%) Defenders (38%) Reactors (34%)

Firm performance affected by match between pay and firm strategies.

(a) Studies of diversification

Gomez-Mejia (1992)

243 HR managers, mfg firms

All employees


Diversification Firm performance affected by match between pay and firm strategies.

Galbraith & Merrill (1991)

79 high technology SBUs

Unit manager

Self-report via survey

BCG-based categories

Pay package design linked to tactical strategies.

Kerr (1985) 20 firms, assorted industries

All employees


Diversification Diversification strategies only weakly related to pay system design.

Napier & Smith (1987)

44 mfg firms

Division managers


Diversification Bonus pay linked to diversification levels; criteria and basis for bonus unrelated to div. strategy.

Hoskisson, Hitt & Hill (1993)

103 Fortune firms

Division managers


Diversification Emphasis shifts from corp. to division level performance as firm div. increases.

Govindarajan & Gupta (1985)

46 SBUs of Fortune 500 firms

Division managers


BCG-based categories

Support for a contingency model between pay plan design, SBU strategy, and performance.

Table 2. Descriptive Statistics

Sample 2

Sample 1

N=516 1 2 3 4 5 6 7 8 9 10 11

26

N=401 Mean 0.31 38.90 12.49 5246

451 1.96 2.72 5.38 4.97 19486 10.42

S.D. 0.46 11.53 9.24 2498 497 0.76 2.16 5.13 0.23 55194 19.12

1 Gender 0.32 0.47 1.000 -0.191 -0.184 -0.185 0.113 0.135 -0.375 -0.279 -0.360 -0.184 -0.196 2 Age 38.44 9.96 -0.206 1.000 0.688 0.073 -0.013 -0.015 0.524 0.395 0.667 0.259 0.200 3 Tenure 13.28 8.67 -0.189 0.592 1.000 -0.011 -0.010 -0.034 0.540 0.429 0.539 0.309 0.264 4 Size Employees 5185 1928 -0.076 0.083 0.000 1.000 -0.593 -0.736 -0.003 -0.297 -0.035 -0.047 -0.076 5 Performance 222 491 -0.082 -0.196 -0.138 0.125 1.000 0.944 0.065 0.454 0.111 0.247 0.338 6 Strat. Orientation 1.87 0.83 -0.094 -0.071 -0.111 0.550 0.810 1.000 0.039 0.444 0.111 0.176 0.245 7 Hierarchy 2.05 1.51 -0.335 0.373 0.340 -0.050 0.130 0.061 1.000 0.853 0.910 0.601 0.582 8 SO x Hierarchy 3.91 3.75 -0.288 0.226 0.148 0.266 0.510 0.542 0.797 1.000 0.786 0.665 0.679 9 Base Salary (log) 4.95 0.18 -0.403 0.537 0.365 0.039 0.130 0.121 0.898 0.786 1.000 0.581 0.557 10 Bonus 17401 71075 -0.154 0.143 -0.034 0.112 0.190 0.179 0.611 0.689 0.646 1.000 0.916 11 Leverage 7.53 20.86 -0.202 0.151 0.009 0.143 0.222 0.204 0.697 0.733 0.694 0.952 1.000

Sample 1 is below diagonal. Correlations > .11 are significant at p < .01

Sample 2 is above diagonal. Correlations > .13 are significant at p < .01

TABLE 3

MEANS FOR COMPENSATION VARIABLES BY STRATEGY AND HIERARCHICAL

POSITION

Strat. Orient. Defender Analyzer Prospector Mean overall

Hierarchy

1 Base salary 100 104 113 105 Bonus 100 148 298 166 Leverage 100 155 296 169 2 Base salary 148 137 144 143 Bonus 337 491 819 532 Leverage 228 368 578 379 3 Base salary 178 184 183 181 Bonus 586 599 1500 910 Leverage 331 333 848 513 4 Base salary 219 240 247 232 Bonus 692 820 5787 1844 Leverage 321 337 2349 768 5 Base salary 266 304 285 284 Bonus 2933 3535 6004 4248 Leverage 1138 1166 2152 1526 6 Base salary 356 393 454 402 Bonus 5151 8045 23730 12594 Leverage 1458 2008 5022 2884 7 Base salary 478 500 575 515 Bonus 14776 12784 45092 23140 Leverage 3225 2599 7730 4347

Mean overall 154 153 182 161 1027 1117 4009 1886 366 402 1146 595 For confidentiality reasons, relative numbers only are presented. Base (=100) is for Strategic Orientation “Defender” at hierarchical level “1” (Employee)

TABLE 4

HIERARCHICAL REGRESSION SUMMARY

Variables Base Pay (Logarithm) Bonus Leverage

Controls Main Effects Full Controls Main Effects Full Controls Main Effects Full

Gender (0=Male) -.26*** -.06*** -.06*** -.13*** .05* .06* -.16*** .02 .03

Age .52*** .31*** .31*** .18*** -.01 .01 .13*** -.05* -.05

Tenure .09** -.09*** -.09*** .02** -.16*** -.15*** .06 -.12*** -.12***

Sample (0=sample 1) .00 -.01 -.02 -.05 -.07** -.11*** -.01 -.04 -.08*

Size Employees -.03 -.01 -.02 .07* .10*** .10*** .09** .11*** .12***

Financial Performance .17*** -.03 -.03 .27*** .18** .15** .34*** .29*** .26***

Strategic Orientation

.11*** .07** .00 -.22*** -.04 -.24***

Hierarchy

.78*** .71*** .70*** .23*** .71*** .30***

Strategy x Hierarchy .09** .58*** .52***

Model Adjusted R2 0.49 0.89 0.89 0.11 0.43 0.48 0.16 0.50 0.53

F-Value 145.51*** 891.78*** 800.09*** 20.38*** 87.90*** 92.54*** 29.67*** 113.36*** 115.17***

Incremental F-Value

1598.19*** 8.40** 256.17*** 73.55** 304.98*** 65.36***

Note: Coefficients are standardized Beta estimates. Significance levels: *p < 0.05; **p < 0.01; ***p < 0.001

TABLE 5

COMPARISON WITH PRIOR FINDINGS

Base pay Bonus Leverage Balkin & Gomez-

Mejia (1990)

Growth strategies had

lower base pay

Growth strategies had

greater use of

incentives

N/A

Rajagopalan &

Finkelstein (1992)

Prospectors had

higher base pay than

Analyzers and

Defenders

Prospectors had

higher bonus pay than

Analyzers and

Defenders

Leverage higher for

Prospectors

Current study • Base pay higher

with change

oriented strategies

• Base pay higher at

upper levels

• Strong interaction

between change

orientation and

hierarchy

• Bonus pay higher

with change

oriented strategies,

but only at upper

levels of hierarchy

• Bonus pay higher

at upper levels of

hierarchy

• Leverage higher

with change

oriented strategies,

but only at upper

levels of hierarchy

• Leverage higher at

upper levels of

hierarchy


FIGURE 1

GRAPHIC MODEL OF INTERACTION EFFECT FOR LOG BASE PAY


FIGURE 2

GRAPHIC MODEL OF INTERACTION EFFECT FOR BONUS


FIGURE 3

GRAPHIC MODEL OF INTERACTION EFFECT FOR LEVERAGE

strategic rewards systems: a contingency model of...

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